CN117113135A - Carbon emission anomaly monitoring and analyzing system capable of sorting and classifying anomaly data - Google Patents
Carbon emission anomaly monitoring and analyzing system capable of sorting and classifying anomaly data Download PDFInfo
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Abstract
The invention discloses a carbon emission anomaly monitoring and analyzing system capable of sorting anomaly data, and relates to the technical field of carbon emission analysis. According to the carbon emission anomaly monitoring and analyzing system capable of sorting and classifying the anomaly data, the enterprise double-carbon data in the carbon emission control system is obtained through the data acquisition module, the data are sent to the data inspection module to judge whether the anomaly exists in the carbon emission data, the anomaly data are sent to the processing and analyzing module to obtain the internal rule and the change trend of the anomaly data, the corresponding regulation and control instruction is sent according to the analysis result of the anomaly data, the improved carbon emission anomaly monitoring and analyzing system can sort and classify the anomaly data, the internal rule and the change trend of the anomaly data are obtained through combination analysis, the regulation and control instruction is sent, and the abnormal enterprise of the carbon emission is promoted to recover to normal.
Description
Technical Field
The invention relates to the technical field of carbon emission analysis, in particular to a carbon emission anomaly monitoring and analyzing system capable of sorting and classifying anomaly data.
Background
In the production process of enterprises, energy consumption is usually generated, so that carbon emission is generated, carbon emission data of the enterprises are required to be monitored, for example, regional monitoring management is carried out due to the fact that the carbon emission is greatly influenced on the environment and is in consideration of protecting the environment, and the data volume is large and the load is processed far beyond the manual work, so that the carbon emission monitoring and analyzing system of the enterprises is used for replacing manual work in the prior art.
The existing monitoring analysis system can automatically monitor the carbon emission condition of enterprises, and warn when the carbon emission data is abnormal, but the standard for judging whether the carbon emission data is abnormal is usually set manually according to experience, and the difference between the enterprise scale and the carbon emission data in the industries is caused to cause the difference between the energy consumption and the carbon emission condition, so that the accuracy of distinguishing the system abnormality is affected.
Disclosure of Invention
In view of the above, the invention provides a carbon emission anomaly monitoring and analyzing system capable of sorting and classifying anomaly data, which can accurately judge whether the anomaly exists in enterprise carbon emission data and analyze the anomaly data in real time, thereby playing a role in timely supervision and targeted regulation.
The technical scheme adopted by the embodiment of the invention for solving the technical problems is as follows:
a carbon emission anomaly monitoring analysis system capable of sorting anomaly data, comprising:
the double-carbon data center is used for storing original enterprise double-carbon data of all enterprises in the carbon management and control system; the method comprises the steps of receiving a query request, calling two-carbon data according to the query request, and sending the two-carbon data to a prediction model creation module;
the prediction model creation module is used for predicting the double-carbon data based on the original enterprise double-carbon data, obtaining prediction data and outputting the prediction data to the data inspection module; the prediction model creation module is specifically configured to execute the following steps:
acquiring the original enterprise double-carbon data from the double-carbon data center, setting training data and prediction data based on the original enterprise double-carbon data, normalizing training sample data, constructing a BP neural network and configuring network parameters, training the BP neural network, and adjusting a network structure according to a training result to form a BP network model;
the carbon grid control system includes, but is not limited to, all businesses being controlled; for providing real-time enterprise bi-carbon data;
the data monitoring module is used for monitoring whether the data retrieval, transmission and updating in the double-carbon data center and the carbon bank management control system are normal or not;
the data acquisition module is used for acquiring the real-time enterprise double-carbon data from the carbon grid control system through equipment and inputting the real-time enterprise double-carbon data into the data inspection module, wherein the acquired real-time enterprise double-carbon data comprises, but is not limited to, enterprise names, energy consumption data, carbon emission data, duty ratio data and emission time period data;
the data checking module is used for comparing the difference between the real-time enterprise double-carbon data and the prediction data so as to check whether the real-time enterprise double-carbon data is abnormal or not, and defining the abnormal real-time enterprise double-carbon data as abnormal data;
the processing analysis module is used for sorting and classifying the abnormal data detected by the data detection module, analyzing the intrinsic law of the abnormal data and obtaining an abnormal data analysis result;
and the regulation and control management module is used for sending regulation and control instructions to enterprises corresponding to the abnormal data in the carbon grid management system according to the analysis result of the abnormal data, so that the enterprises corresponding to the abnormal data can make corresponding carbon emission regulation control according to the regulation and control instructions, and data return to normal is promoted.
Preferably, the first output end of the data monitoring module is connected with the dual-carbon data center, the second output end of the data monitoring module is connected with the carbon grid control system, and the dual-carbon data center and the carbon grid control system operate independently of each other and are not interfered with each other.
Preferably, the input end of the dual-carbon data center is connected with the output end of the data checking module, and the data stored in the dual-carbon data center comprises normal data, abnormal data, original data and operation and maintenance data.
Preferably, the data checking module comprises a data comparing unit, a difference analyzing unit and an abnormality judging unit, wherein the output end of the data comparing unit is connected with the input end of the difference analyzing unit, and the output end of the difference analyzing unit is connected with the input end of the abnormality judging unit.
Preferably, a first input end of the data comparison unit is connected with the BP network model and used for receiving the prediction data transmitted by the BP network model, and a second input end of the data comparison unit is connected with the data acquisition module and used for receiving the data transmitted by the data acquisition module in real time.
Preferably, the data comparison unit, the difference analysis unit and the abnormality discrimination unit have time sequence; the data comparison unit obtains data differences by comparing the predicted data with the real-time enterprise double-carbon data and sends the data differences to the difference analysis unit; analyzing the data difference by the difference analysis unit to obtain a data difference size; and then the abnormality judging unit judges whether the data difference is in a normal range according to the data difference size.
Preferably, the discrimination formula of the abnormality discrimination unit is as follows:
wherein CV is a difference coefficient, X_pd is prediction data, X_rd is carbon number data, i is any integer from 1 to n, n is the total number of enterprises, k is a normal range value, S is an abnormal data discrimination result, and S1 and S2 are discrimination results 1 and 2 respectively.
Preferably, the two abnormal judging results are a judging result s1 and a judging result s2, wherein the judging result s1 indicates that the data difference is in a normal range, the real-time enterprise dual-carbon data is not abnormal and is output as normal data, and the judging result s2 indicates that the data difference exceeds the normal range, indicates that the real-time enterprise dual-carbon data is abnormal and is output as abnormal data.
Preferably, the processing analysis module comprises a data sorting unit, a data classifying unit and an anomaly analysis unit, wherein the data sorting unit is used for receiving the anomaly data and sorting the anomaly data, the data classifying module is used for classifying the anomaly data according to data characteristics, the anomaly analysis unit is used for analyzing the anomaly data, and the anomaly analysis unit is used for sequentially executing comparison analysis and trend analysis.
Preferably, the use flow of the carbon emission anomaly monitoring and analyzing system capable of sorting the anomaly data is as follows:
step one, the prediction model creation module sends a request to the double-carbon data center to acquire original enterprise double-carbon data, and a BP network model is built on the basis of the original enterprise double-carbon data;
step two, acquiring real-time enterprise double-carbon data in the carbon grid control system through the data acquisition module and sending the real-time enterprise double-carbon data to the data inspection module, wherein after the data comparison unit receives the real-time enterprise double-carbon data and the predicted data transmitted by the BP network model, the data difference is obtained through data comparison and sent to the difference analysis unit, the difference analysis unit analyzes the data difference size to obtain the data difference size, and then the difference judgment unit judges whether the data difference is in a normal range according to the data difference size so as to judge whether the real-time enterprise double-carbon data is abnormal data or not;
step three, the abnormal data are sent to a processing analysis module, the abnormal data are received and sorted through the data sorting unit, then the data classification module classifies the abnormal data according to data characteristics, and then the abnormal analysis unit sequentially executes comparison analysis and trend analysis commands to analyze and obtain abnormal data analysis results, wherein the abnormal data analysis results comprise internal rules and change trends of the abnormal data;
and step four, the regulation and control management module sends a regulation and control instruction to an enterprise corresponding to the abnormal data in the carbon grid management system according to the analysis result of the abnormal data, so that the enterprise corresponding to the abnormal data can make corresponding carbon emission regulation control according to the regulation and control instruction, and data return to normal is promoted.
According to the technical scheme, the carbon emission anomaly monitoring and analyzing system capable of sorting and classifying the anomaly data provided by the embodiment of the invention has the following beneficial effects: according to the invention, the data of the double-carbon data center is acquired through the prediction model creation module, so that a BP network model is established, enterprise double-carbon data in the carbon grid control system is acquired through the data acquisition module, the enterprise double-carbon data is transmitted to the data inspection module to judge whether the carbon grid data is abnormal or not, the abnormal data is transmitted to the processing analysis module to obtain an internal rule and a change trend of the abnormal data, then the regulation management module transmits a regulation command to an enterprise with data abnormal conditions in the carbon grid control system according to an abnormal data analysis result to realize carbon grid regulation, the improved carbon emission abnormal monitoring analysis system can not only accurately judge whether the carbon grid data of the enterprise is abnormal or not through the cooperation of the model and the formula, but also can sort the abnormal data in a sorting way, and the internal rule and the change trend of the abnormal data are obtained through the combination analysis, so that the regulation command is transmitted, and the abnormal carbon emission of the enterprise is promoted to restore to normal.
Drawings
FIG. 1 is a schematic diagram of an overall operation flow of a carbon emission anomaly monitoring and analyzing system capable of sorting anomaly data according to the present invention;
FIG. 2 is a schematic diagram of a two-carbon data center-carbon grid control system of a carbon emission anomaly monitoring and analyzing system capable of sorting anomaly data according to the present invention;
FIG. 3 is a schematic diagram of a data inspection module of a system for monitoring and analyzing abnormal carbon emissions, which can sort abnormal data according to the present invention;
FIG. 4 is a schematic diagram of a process analysis module of a system for monitoring and analyzing abnormal carbon emissions, which can sort abnormal data according to the present invention;
fig. 5 is a schematic diagram of a BP network model creation flow of a carbon emission anomaly monitoring and analyzing system capable of sorting and classifying anomaly data according to the present invention.
Detailed Description
The technical scheme and technical effects of the present invention are further elaborated below in conjunction with the drawings of the present invention.
As shown in fig. 1 to 5, a carbon emission anomaly monitoring and analyzing system capable of sorting anomaly data comprises:
the double-carbon data center is used for storing original enterprise double-carbon data of all enterprises in the carbon management and control system; the method comprises the steps of receiving a query request, calling two-carbon data according to the query request, and sending the two-carbon data to a prediction model creation module; raw business two-carbon data includes, but is not limited to, business name, energy consumption data, carbon emission data, duty cycle data, and emission time period data;
the prediction model creation module is used for predicting the double-carbon data based on the original enterprise double-carbon data, obtaining prediction data and outputting the prediction data to the data inspection module; the prediction model creation module is specifically configured to execute the following steps:
acquiring the original enterprise double-carbon data from the double-carbon data center, setting training data and prediction data based on the original enterprise double-carbon data, normalizing training sample data, constructing a BP neural network and configuring network parameters, training the BP neural network, and adjusting a network structure according to a training result to form a BP network model;
the carbon grid control system includes, but is not limited to, all businesses being controlled; for providing real-time enterprise bi-carbon data;
the data monitoring module is used for monitoring whether the data retrieval, transmission and updating in the double-carbon data center and the carbon bank management control system are normal or not;
the data acquisition module is used for acquiring the real-time enterprise double-carbon data from the carbon grid control system through equipment and inputting the real-time enterprise double-carbon data into the data inspection module, wherein the acquired real-time enterprise double-carbon data comprises, but is not limited to, enterprise names, energy consumption data, carbon emission data, duty ratio data and emission time period data; the first output end of the data monitoring module is connected with the double-carbon data center, the second output end of the data monitoring module is connected with the carbon grid control system, and the double-carbon data center and the carbon grid control system operate independently of each other and are not interfered with each other;
the data checking module is used for comparing the difference between the real-time enterprise double-carbon data and the prediction data so as to check whether the real-time enterprise double-carbon data is abnormal or not, and defining the abnormal real-time enterprise double-carbon data as abnormal data; the input end of the double-carbon data center is connected with the output end of the data checking module, and the data stored in the double-carbon data center comprises normal data, abnormal data, original data and operation and maintenance data;
the data checking module comprises a data comparing unit, a difference analyzing unit and an abnormality judging unit, wherein the output end of the data comparing unit is connected with the input end of the difference analyzing unit, and the output end of the difference analyzing unit is connected with the input end of the abnormality judging unit. The first input end of the data comparison unit is connected with the BP network model and used for receiving the prediction data transmitted by the BP network model, and the second input end of the data comparison unit is connected with the data acquisition module and used for receiving the data transmitted by the data acquisition module in real time. Here, the data transmitted in real time by the data acquisition module refers to real-time enterprise double-carbon data;
the data comparison unit, the difference analysis unit and the abnormality discrimination unit have time sequence; the data comparison unit obtains data differences by comparing the predicted data with the real-time enterprise double-carbon data and sends the data differences to the difference analysis unit; analyzing the data difference by the difference analysis unit to obtain a data difference size; and then the abnormality judging unit judges whether the data difference is in a normal range according to the data difference size.
The discrimination formula of the abnormality discrimination unit is as follows:
wherein CV is a difference coefficient, X_pd is prediction data, X_rd is real-time enterprise carbon line data, i represents any integer from 1 to n, n represents the total number of enterprises, k is a normal range value, S is an abnormal data judging result, and S1 and S2 represent judging results 1 and 2 respectively.
The number of the abnormal judging results is two, namely a judging result s1 and a judging result s2, wherein the judging result s1 indicates that the data difference is in a normal range, the real-time enterprise double-carbon data is abnormal and is output as normal data, and the judging result s2 indicates that the data difference exceeds the normal range, indicates that the real-time enterprise double-carbon data is abnormal and is output as abnormal data.
The processing analysis module comprises a data sorting unit, a data classifying unit and an abnormality analysis unit, wherein the data sorting unit is used for receiving and sorting abnormal data, the data classifying module is used for classifying the abnormal data according to data characteristics, the abnormality analysis unit is used for analyzing the abnormal data, and the abnormality analysis unit is used for sequentially executing comparison analysis and trend analysis.
The processing analysis module is used for sorting and classifying the abnormal data detected by the data detection module, analyzing the intrinsic law of the abnormal data and obtaining an abnormal data analysis result;
and the regulation and control management module is used for sending regulation and control instructions to enterprises corresponding to the abnormal data in the carbon grid management system according to the analysis result of the abnormal data, so that the enterprises corresponding to the abnormal data can make corresponding carbon emission regulation and control according to the regulation and control instructions, and the data of the enterprises are promoted to return to normal.
The foregoing references to the enterprise double carbon data include, but are not limited to, enterprise name, energy consumption data, carbon emission data, duty ratio data, and emission time period data, and it is understood that the data involved in a single CV calculation may be a collection of all types of data of the enterprise, or may be a collection of single or several types of data (i.e., whole analysis, partial combination analysis, or analysis-by-analysis), and thus, the data range identified as abnormal data after analysis by a single CV result may be all of the data in the real-time enterprise carbon emission data, or may be some of the real-time enterprise carbon emission data, and thus, there may be differences in the data types of the abnormal data stored in the double carbon data center.
In summary, referring to fig. 1 to 5, the carbon emission anomaly monitoring and analyzing system capable of sorting and classifying the anomaly data is characterized in that the usage flow of the carbon emission anomaly monitoring and analyzing system capable of sorting and classifying the anomaly data is as follows:
step one, a prediction model creation module sends a request to a double-carbon data center, original double-carbon data of an enterprise are obtained, and a BP network model is built on the basis of the double-carbon data;
acquiring enterprise double-carbon data in a carbon grid control system through a data acquisition module, sending the enterprise double-carbon data to a data inspection module, acquiring data differences through data comparison after a data comparison unit receives prediction data transmitted by a BP network model and real-time data transmitted by the data acquisition module, sending the data differences to a difference analysis unit, analyzing the data differences to obtain the size, and then calculating and judging whether the data is abnormal or not through a formula by the difference analysis unit;
step three, the abnormal data are sent to a processing analysis module, the abnormal data are received and sorted through a data sorting unit, then the data sorting module sorts the abnormal data according to the data characteristics, and then the abnormal analysis unit sequentially executes comparison analysis and trend analysis commands to analyze and obtain the internal rules and the change trend of the abnormal data;
and step four, the regulation and control management module sends a regulation and control instruction to an enterprise with data abnormality in the carbon grid control system according to the abnormal data analysis result, and the enterprise receives the regulation and control instruction and then performs regulation and control according to the instruction.
The embodiments of the invention have been presented for purposes of illustration and description, and are not intended to be exhaustive or limited to the invention in the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, and to enable others of ordinary skill in the art to understand the invention for various embodiments with various modifications as are suited to the particular use contemplated.
Claims (10)
1. A carbon emission anomaly monitoring analysis system capable of sorting anomaly data, comprising: the double-carbon data center is used for storing original enterprise double-carbon data of all enterprises in the carbon management and control system; the method comprises the steps of receiving a query request, calling two-carbon data according to the query request, and sending the two-carbon data to a prediction model creation module; the prediction model creation module is used for predicting the double-carbon data based on the original enterprise double-carbon data, obtaining prediction data and outputting the prediction data to the data inspection module; the prediction model creation module is specifically configured to execute the following steps:
acquiring the original enterprise double-carbon data from the double-carbon data center, setting training data and prediction data based on the original enterprise double-carbon data, normalizing training sample data, constructing a BP neural network and configuring network parameters, training the BP neural network, and adjusting a network structure according to a training result to form a BP network model;
the carbon grid control system includes, but is not limited to, all businesses being controlled; for providing real-time enterprise bi-carbon data;
the data monitoring module is used for monitoring whether the data retrieval, transmission and updating in the double-carbon data center and the carbon bank management control system are normal or not;
the data acquisition module is used for acquiring the real-time enterprise double-carbon data from the carbon grid control system through equipment and inputting the real-time enterprise double-carbon data into the data inspection module, wherein the acquired real-time enterprise double-carbon data comprises, but is not limited to, enterprise names, energy consumption data, carbon emission data, duty ratio data and emission time period data;
the data checking module is used for comparing the difference between the real-time enterprise double-carbon data and the prediction data so as to check whether the real-time enterprise double-carbon data is abnormal or not, and defining the abnormal real-time enterprise double-carbon data as abnormal data;
the processing analysis module is used for sorting and classifying the abnormal data detected by the data detection module, analyzing the intrinsic law of the abnormal data and obtaining an abnormal data analysis result;
and the regulation and control management module is used for sending regulation and control instructions to enterprises corresponding to the abnormal data in the carbon grid management system according to the analysis result of the abnormal data, so that the enterprises corresponding to the abnormal data can make corresponding carbon emission regulation control according to the regulation and control instructions, and data return to normal is promoted.
2. The system of claim 1, wherein a first output of the data monitoring module is connected to the dual carbon data center, and a second output of the data monitoring module is connected to the carbon grid control system, the dual carbon data center and the carbon grid control system operating independently of each other and not interfering with each other.
3. The system for monitoring and analyzing abnormal carbon emissions capable of sorting abnormal data according to claim 2, wherein the input end of the dual-carbon data center is connected to the output end of the data inspection module, and the data stored in the dual-carbon data center includes normal data, abnormal data, raw data and operation and maintenance data.
4. The system for monitoring and analyzing abnormal carbon emissions capable of sorting abnormal data according to claim 3, wherein the data inspection module comprises a data comparison unit, a difference analysis unit and an abnormality discrimination unit, wherein the output end of the data comparison unit is connected with the input end of the difference analysis unit, and the output end of the difference analysis unit is connected with the input end of the abnormality discrimination unit.
5. The system for monitoring and analyzing abnormal carbon emissions capable of sorting abnormal data according to claim 4, wherein a first input end of the data comparison unit is connected with the BP network model for receiving the predicted data transmitted by the BP network model, and a second input end of the data comparison unit is connected with the data acquisition module for receiving the data transmitted by the data acquisition module in real time.
6. The system for monitoring and analyzing abnormal carbon emissions capable of sorting abnormal data according to claim 5, wherein the data comparison unit, the difference analysis unit and the abnormality discrimination unit have time-series property; the data comparison unit obtains data differences by comparing the predicted data with the real-time enterprise double-carbon data and sends the data differences to the difference analysis unit; analyzing the data difference by the difference analysis unit to obtain a data difference size; and then the abnormality judging unit judges whether the data difference is in a normal range according to the data difference size.
7. The system for monitoring and analyzing abnormal carbon emissions capable of sorting abnormal data according to claim 6, wherein the discrimination formula of the abnormality discrimination unit is as follows:
wherein CV is a difference coefficient, X_pd is prediction data, X_rd is real-time enterprise carbon line data, i represents any integer from 1 to n, n represents the total number of enterprises, k is a normal range value, S is an abnormal data judging result, and S1 and S2 represent judging results 1 and 2 respectively.
8. The system for monitoring and analyzing abnormal carbon emissions capable of sorting abnormal data according to claim 7, wherein the abnormal discrimination results are two and two, namely a discrimination result s1 and a discrimination result s2, the discrimination result s1 indicates that the data difference is within a normal range, the real-time enterprise dual-carbon data is abnormal and is output as normal data, the discrimination result s2 indicates that the data difference exceeds the normal range, the real-time enterprise dual-carbon data is abnormal and is output as abnormal data.
9. The system for monitoring and analyzing abnormal carbon emissions capable of sorting abnormal data according to claim 8, wherein the processing and analyzing module comprises a data sorting unit, a data classifying unit and an abnormal analyzing unit, wherein the data sorting unit is used for receiving and sorting abnormal data, the data classifying module is used for classifying the abnormal data according to data characteristics, the abnormal analyzing unit is used for analyzing the abnormal data, and the abnormal analyzing unit sequentially performs comparison analysis and trend analysis.
10. The abnormal carbon emission monitoring and analyzing system capable of sorting abnormal data according to any one of claims 1 to 9, wherein the use flow of the abnormal carbon emission monitoring and analyzing system capable of sorting abnormal data is as follows:
step one, the prediction model creation module sends a request to the double-carbon data center to acquire original enterprise double-carbon data, and a BP network model is built on the basis of the original enterprise double-carbon data;
step two, acquiring real-time enterprise double-carbon data in the carbon grid control system through the data acquisition module and sending the real-time enterprise double-carbon data to the data inspection module, wherein after the data comparison unit receives the real-time enterprise double-carbon data and the predicted data transmitted by the BP network model, the data difference is obtained through data comparison and sent to the difference analysis unit, the difference analysis unit analyzes the data difference size to obtain the data difference size, and then the difference judgment unit judges whether the data difference is in a normal range according to the data difference size so as to judge whether the real-time enterprise double-carbon data is abnormal data or not;
step three, the abnormal data are sent to a processing analysis module, the abnormal data are received and sorted through the data sorting unit, then the data classification module classifies the abnormal data according to data characteristics, and then the abnormal analysis unit sequentially executes comparison analysis and trend analysis commands to analyze and obtain abnormal data analysis results, wherein the abnormal data analysis results comprise internal rules and change trends of the abnormal data;
and step four, the regulation and control management module sends a regulation and control instruction to an enterprise corresponding to the abnormal data in the carbon grid management system according to the analysis result of the abnormal data, so that the enterprise corresponding to the abnormal data can make corresponding carbon emission regulation control according to the regulation and control instruction, and data return to normal is promoted.
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| CN117350441A (en) * | 2023-12-06 | 2024-01-05 | 国网山东省电力公司烟台供电公司 | Efficiency-improving and carbon-reducing operation optimizing system and method for public building |
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| CN117350441A (en) * | 2023-12-06 | 2024-01-05 | 国网山东省电力公司烟台供电公司 | Efficiency-improving and carbon-reducing operation optimizing system and method for public building |
| CN117350441B (en) * | 2023-12-06 | 2024-03-01 | 国网山东省电力公司烟台供电公司 | Efficiency-improving and carbon-reducing operation optimizing system and method for public building |
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